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Modelling Agricultural Production Systems using Mathematical Programming

Ekman, Sone (2002). Modelling Agricultural Production Systems using Mathematical Programming. Diss. (sammanfattning/summary) Uppsala : Sveriges lantbruksuniv., Acta Universitatis Agriculturae Sueciae. Agraria, 1401-6249 ; 351
ISBN 91-576-6163-4
[Doctoral thesis]

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This thesis focuses on the economics of changing farm-level production practices. It is recognised that many decisions made in a firm or a market are interrelated. Economic analyses aiming at predicting behaviour or recommending on alternatives for action need to account for these relations, otherwise the results and prescriptions will be misleading. In each of the four articles a mathematical programming model of an agricultural production system is developed, and empirical analyses are performed using Swedish data. The first article analyses aggregate effects of on-farm potato processing, utilising a partial equilibrium framework. An analysis of the Swedish potato market shows that, in more densely populated regions, on-farm processing is a part of a socially optimal industry structure. Increased import competition results in a larger share of domestic potatoes being processed at the farm-level. In article II, alternative tillage systems for grain production are evaluated. A mathematical programming model with simultaneous selection of crop rotation, machinery investments and scheduling of tillage and drilling operations is developed, utilising discrete stochastic programming to model field time variability. The empirical results show that a tillage system characterised by lower machinery capital and labour requirements may be as profitable as a conventional system. The model from article II is further developed in article III and IV. Article III recognises that policy measures aiming at reducing nitrogen leaching from crop production often have indirect effects. As an example, the empirical results show that subsidies to catch crops and spring ploughing provide an incentive to increase the area of spring crops, such that these subsidies may increase rather than reduce nitrogen emissions. In article III it is also concluded that cost-effective nitrogen abatement requires a mix of various adjustments of production practices, rather than a focus on a few measures. Article IV analyses whether it is necessary to account for environmental and economic risk when analysing measures to reduce nitrogen leaching in crop production. Considering environmental risk increases abatement costs. However, it appears that the benefits from explicitly accounting for nitrogen leaching variability (environmental risk) in the model are rather small, since the majority of the environmental risk is non-diversifiable. The benefits from including economic risk associated with income variability seem

Authors/Creators:Ekman, Sone
Title:Modelling Agricultural Production Systems using Mathematical Programming
Series Name/Journal:Acta Universitatis Agriculturae Sueciae. Agraria
Year of publishing :November 2002
Number of Pages:26
ALLI. Ekman, S. & Andersson, H. (1998). The economics of on-farm processing: model development and an empirical analysis. Agricultural Economics 18: 177-189. II. Ekman, S. (2000). Tillage system selection: a mathematical programming model incorporating weather variability. Journal of Agricultural Engineering Research 77: 267-276. III. Ekman, S. (2002). Cost-effective nitrogen leaching reduction as influenced by linkages between farm-level decisions. (Manuscript). IV. Ekman, S. (2002). Reduction of farm-level nitrogen leaching in the presence of environmental and economic risk. (Manuscript).
Place of Publication:Uppsala
ISBN for printed version:91-576-6163-4
Publication Type:Doctoral thesis
Full Text Status:Public
Agris subject categories.:E Economics, development, and rural sociology > E10 Agricultural economics and policies
Subjects:Not in use, please see Agris categories
Agrovoc terms:agricultural economics, production factors, farm management, optimization methods, input output analysis, diversification
Keywords:crop rotation, discrete stochastic programming (DSP), diversification, economics, farm management, farm models, machinery investments, mathematical programming, nitrogen leaching, nonpoint pollution, on-farm processing, policy analysis, risk, sector models, tillage systems
Permanent URL:
ID Code:88
Department:(NL, NJ) > Dept. of Economics
Deposited By: Sone Ekman
Deposited On:09 Dec 2002 00:00
Metadata Last Modified:02 Dec 2014 10:01

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